Passive Identification is Non Stationary Objects With Closed Loop Control

7th International Scientific Practical Conference "Innovative Technologies in Engineering"

Dyadik, Valeriy F.^1 ; Nadezhdin, Igor S.^1 ; Goryunov, Alexey G.^1 ; Manenti, Flavio^2

Tomsk Polytechnic University, Institute of Physics and Technology, Department of Electronics and Automation of Nuclear Plants, Lenina St 30, Tomsk

634050, Russia^1

Politecnico di Milano, Dipartimento di Chimica, Materiali e Ingegneria Chimica Giulio Natta, Piazza Leonardo da Vinci 32, Milano

20133, Italy^2

关键词: Automated control systems;    Closed-loop control;    Controlled variables;    Conventional control systems;    Hybrid fuzzy-PID control;    Identification procedure;    Non-stationary objects;    Regulatory control systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/142/1/012047/pdf
DOI  :  10.1088/1757-899X/142/1/012047

来源: IOP

【 摘 要 】

Typically chemical processes have significant nonlinear dynamics, but despite this, industry is conventionally still using PID-based regulatory control systems. Moreover, process units are interconnected, in terms of inlet and outlet material/energy flows, to other neighbouring units, thus their dynamic behaviour is strongly influenced by these connections and, as a consequence, conventional control systems performance often proves to be poor. However, there a hybrid fuzzy PID control logic, whose tuning parameters are provided in real time. The fuzzy controller tuning is made on the basis of Mamdani controller, also exploiting the results coming from an identification procedure that is carried on when an unmeasured step disturbance of any shape affects the process behaviour. This paper presents procedure for identifying technological object control in a closed loop, i. e. that operates the automated control system. The variation in the controlled variable, caused by the change of the nonmeasurable disturbance, is considered the initial signal for the identification procedure. The parameters of the control object are found by optimization method Levenberg-Marquardt.